The aim of this research is to investigate the attributes of small networks of synaptically connected mammalian neurons, formed in microcultures of approximately 10 cells. The development of these networks will be observed, and studies will be made to uncover systematic patterns of connectivity. Subsequently, the effects of chronically imposed patterns of activity on the networks will be studied, as well as the effects of ablation of one or more cells. A system developed in this laboratory will be employed to noninvasively stimulate and record from a microculture so as to determine the synaptic connectivity at a particular time, and then for the same microculture at later times. This system, which is now in use, employs a voltage-sensitive dye for recording and microcircuit culture dishes for stimulation. The culture dishes incorporate an array of 61 extracellular stimulating electrodes under the small area covered by a microculture. With these electrodes, any cell may be stimulated, and the stimulation may be applied chronically while the culture grows. The response to a stimulus of all the cells in a culture can be simultaneously measured with the aid of the dye, which detects changes in cell membrane potentials. The proposed investigation is designed to elucidate basic principles of connectivity and plasticity among the neurons in a network. Initially, simple purely excitatory networks formed by sympathetic neurons will be studied. Afterward, complex cultures of CNS neurons will be examined. Among the experiments will be measurements of the effect on synaptic strength of simultaneous excitation of a pair of pre- and postsynaptic cells, often hypothesized to be a method for network adaptation or learning. Also, experiments will be performed to assess the role of activity when two presynaptic neurons compete at a common postsynaptic cell. These studies, as well as a variety of others, will capitalize on the unique opportunities afforded by the noninvasive system for studying the effects of activity on both cellular and network properties.